21–30 of 118 posts
I have never understood the appeal of this. You can generate good looking presentations, but that is all. Is any real science done with this or is it the Powerpoint for PyCon talks?
I have never understood the appeal of this. You can generate good looking presentations, but that is all. Is any real science done with this or is it the Powerpoint for PyCon talks?
I have never understood the appeal of this. You can generate good looking presentations, but that is all. Is any real science done with this or is it the Powerpoint for PyCon talks?
People use it for two reasons: a) because they need to get those graphs on the screen and this is the only way b) running ML code on a remote, beefier server.
I have never understood the appeal of this. You can generate good looking presentations, but that is all. Is any real science done with this or is it the Powerpoint for PyCon talks?
Advantages...no setup on the students side (+they get reliable compute remotely) and we can prepare notebooks highlighting certain concepts. Text cells are usefull for explaining stuff so they can work through some notebooks by themselves. Students can also easily share notebooks with us if they have any questions/issues.
I also use notebooks for data exploration, training initial test models etc. etc. Very useful. I'd say >50% of my ML related work gets done in notebooks.
I have never understood the appeal of this. You can generate good looking presentations, but that is all. Is any real science done with this or is it the Powerpoint for PyCon talks?
Like everything else in the Python ecosystem, it's half-baked and not composable. People use it for two reasons: a) because they need to get those graphs on the screen and this is the only way b) running ML code on a remote, beefier server.
This is interesting! Looking forward to testing the purple theme I use [1]. I wonder if extension developers will need to maintain three sets of instructions now? JupyterLab, Jupyter Notebook >= 7, and Jupyter Notebook [1] https://github.com/shahinrostami/theme-purple-please
> Both Jupyter Notebook and JupyterLab are widely used across data science, machine learning, computational research, and education. Are they though? Does anyone actually use JupyterLab by choice? From what I've seen people love Jupyter Notebook but find JupyterLab misses the mark (and this is certainly my experience).
I primarily use Jupyter Lab. I have some frustrations but I generally like being able to manage multiple kernels from one notebook, having multiple views into one notebook, having context-sensitive help, and having some of the other features that were only in Lab. That being said, I'm glad they've switched course and continue to work on Notebook once it became clear some people preferred it to Lab. With some of the a…
I thought Notebook is getting deprecated. What is the difference between Jupyter Lab and Jupyter Notebook ? Are these developed by two completely different teams? Why maintain two code bases?
Previously there was "Jupyter Notebook". Then they separately wrote JupyterLab (creating a brand new implementation of notebooks for it). Now, they're taken the JupyterLab notebook code and used it to replace "Jupyter Notebook".